| 光谱学与光谱分析 |
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| Data Analysis of Laser Desorption/Ionization Mass Spectrum of Atmospheric Aerosol Particles Using Fuzzy Clustering Algorithms |
| GUO Xiao-yong,FANG Li,ZHAO Wen-wu,GU Xue-jun,ZHENG Hai-yang,ZHANG Wei-jun |
| Lab of Environmental Spectroscopy, Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Sciences, Hefei 230031, China |
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Abstract On-line measurement of size and composition of single particle using an aerosol time-of-flight Laser mass spectrometry (ATOFLMS) had been designed in our lab.Each particle’s aerodynamic diameter is determined by measuring the delay time between two continuous-wave lasers, A Nd∶YAG laser desorbs and ionizes molecules from the particle, and the time-of-flight mass spectrometer collects a mass spectrum of the generated ions.Then the composition of single particle is obtained.ATOFLMS generates large amount of data during the process period.How to process these data and extract valuable information is one of the key problems for the ATOFLMS.In this paper, the fuzzy clustering used to classify large numbers of mass spectral of air indoor by an ATOFLMS.Each revised spectrum is converted to a normalized 300-point vector, each point representing one mass unit.Then the positive ion mass spectra of a single particle are described as 300-dimensional data vectors using the ion masses as dimensions and the ion signal peak areas as values.The data vectors of all particles measured are written into a classification matrix.Each spectrum’s data was stored as one row in this matrix.The Fuzzy c-means algorithm is an iterative method starting the calculation with random class centers to find a substructure in the data.The procedure works in such a way that finally similar objects (particle spectra) have a minimum distance between their corresponding data vectors, on the one hand, and to the center of a cluster, on the other hand.So the aim of the iteration is to find local minima in the N-dimensional space where N is the number of evaluated peak masses.The particle data used in this study were collected over a period one day in Hefei.During the campaign, inorganic salts, mineral particles, and carbonaceous particles, with varying degrees of secondary components, were identified.The detection results of particle size exhibit that aerosol is predominanantly in the form of fine particles, and the particles whose diameter larger than 1 μm are scare.The particles whose diameter less than 1 μm are make up of 95% of the total particles, and these particles are major distributed in 0.4-0.8 μm.
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Received: 2007-05-10
Accepted: 2007-08-20
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Corresponding Authors:
GUO Xiao-yong
E-mail: xyguo@aiofm.ac.cn
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[1] Molina M J, Angew.Chem.Int.Ed.Engl, 1996, 35：1778.
[2] Moren F, Dolovich M B, Newhouse M T, et al.Aerosols in Medicine：Principles, Diagnosis and Therapy, 2nd edition, Amsterdam：Elsevier, 1993, 321.
[3] Dockery D W, Pope III C A.Annu.Rev.Public Health, 1994, 15：107.
[4] LIAN Yue, LIU Wen-qing, LU Jian-chun, et al(连 悦, 刘文清, 鹿建春, 等).Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2006, 26(1)：198.
[5] Johnston M V, Wexler A S.Anal.Chem.1995, 67：721A.
[6] Peter T.Science, 1996, 273：1352.
[7] Bezdek J C.Pattern Recognition with Fuzzy Objective Function Algorithms, New York：Plenum Press, 1981.
[8] XIA Zhu-hong, FANG Li, ZHENG Hai-yang, et al(夏柱红, 方 黎, 郑海洋，等).Chinese Journal of Analytical Chemistry(分析化学), 2004, 32(7)：973.
[9] GUO Xiao-yong, ZHOU Liu-zhu, ZHAO Wen-wu, et al(郭晓勇, 周留柱，赵文武，等).Chinese Journal of Quantum Electronics(量子电子学报), 2006, 23(2)：217.
[10] Hinz K P, Greweling M, Drews F, et al.J.Am.Soc.Mass.Spectrom., 1999, 10：648.
[11] Davies D L, Bouldin D W.IEEE Trans.Patt.Anal.Machine Intell., 1979, PAMI-1：224.
[12] Held A, Hinzb K P, Trimbornb A, et al.Journal of Aerosol Science, 2002, 33：581.
[13] Gundel L A, Benner W H, Hansen A D.Atmospheric Environment, 1994, 28：2715. |
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